We present a new class of problems, called resource-bounded information gathering for correlation clustering. Our goal is to perform correlation clustering under circumstances in which accuracy may be improved by augmenting the given graph with additional information. This information is obtained by querying an external source under resource constraints. The problem is to develop the most effective query selection strategy to minimize some loss function on the resulting partitioning. We motivate the problem using an entity resolution task. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Kanani, P., & McCallum, A. (2007). Resource-bounded information gathering for correlation clustering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4539 LNAI, pp. 625–627). Springer Verlag. https://doi.org/10.1007/978-3-540-72927-3_46
Mendeley helps you to discover research relevant for your work.